Senior Data Analyst / Data Scientist (Flexible Working)
JAC Recruitment
Date: 6 days ago
City: Remote
Contract type: Full time
Remote
A retail company in Malaysia is looking for a Senior Data Analyst/Data Scientist, with experience in data analysis, business intelligence, or a similar role. This role has flexible working arrangements which you can arrange your own working location and time.
Key Responsibilities
Data Extraction and Analysis:
Key Responsibilities
Data Extraction and Analysis:
- Collect, clean, and analyze large datasets related to operations, commerce, user behaviors, retention, operational efficiencies, user experience, employee experience, redundancies, and more.
- Utilize statistical methods and tools to interpret data sets, paying particular attention to trends and patterns that could be valuable for diagnostic and predictive analytics.
- Focus on commercial data (marketing, sales) to provide insights on customer acquisition, retention, revenue growth, and market trends.
- Analyze non-commercial data (operations, maintenance, customer advocacy, inventory) to identify areas for operational improvements and efficiency gains.
- Develop and maintain dashboards, reports, and visualizations to effectively communicate findings to management and stakeholders.
- Present complex information in a clear and concise manner, making data accessible and understandable to non-technical team members.
- Gather and analyze industry data to understand market dynamics, competitor performance, and external factors affecting the business.
- Use external data sources to augment internal data, providing a comprehensive view that aids in strategic planning and decision-making.
- Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or a related field.
- Minimum 3 years of experience in data analysis, business intelligence, or a similar role.
- Proficiency in data analysis tools and languages such as SQL, Python, R, and experience with data visualisation tools like Tableau or Power BI.
- Familiarity with data warehousing concepts and ETL processes.
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